Project Summary Cardiovascular disease (CVD) remains one of the most prevalent diseases among the adult population and disproportionately affects low-income populations. Medicaid, the primary source of health insurance for low- income adults, plays a critical role in facilitating care for adults with CVD. Medicaid beneficiaries have traditionally had difficulty obtaining timely access to specialists. To improve access to physicians and health services, state Medicaid agencies have increasingly contracted with managed care organizations (MCO), who in turn contract with networks of physicians to facilitate access to care. While regulations have standardized the benefits, formularies, and cost sharing rules that plans must adhere to in Medicaid; MCOs have considerable latitude to design and modify their physician networks. Consequently, the volume of cardiologists and amount of physician turnover (churn) vary considerably across plans in the same market. We hypothesize that these two features of networks, (1) network breadth and (2) network churn, are particularly impactful in influencing patterns of care and outcomes for Medicaid managed care beneficiaries with CVD. Cardiac patients in narrower networks may have to travel further, wait longer for appointments, and find a doctor they like from a smaller set of options. Network churn may disrupt the relationships between patients with complex conditions who are actively engaged in care and their primary care physicians or cardiologists. Although design of physician networks directly influences how low-income populations access care for cardiovascular conditions, there has been no investigation on how they impact the receipt of recommended care and outcomes. To date, network adequacy regulations have been uninformed by the way that beneficiaries experience care and disconnected from health care outcomes. Our objective, in this application, is to estimate the causal impact of cardiovascular network design on health care outcomes for Medicaid patients with CVD. We propose to do this via two innovations. First, we use a novel dataset which merges detailed physician network data with administrative Medicaid data from several states. Second, we leverage the fact that a substantial fraction of Medicaid enrollees that don't actively choose a plan are randomly-assigned to health plans, allowing us to estimate the impact of physician network design on cardiovascular care and outcomes using a randomized- controlled design, the gold standard in social science research. Specifically, our aims are to (1) Use patient random- assignment to estimate the causal effect of network breadth on patterns of treatment, use and outcomes for patients newly diagnosed with CVD, (2) Determine how physician exits impact patterns of treatment, use and outcomes for patients with previously diagnosed (existing) CVD, and (3) Use simulation models to inform adequacy standards for specialty physician networks of Medicaid MCOs. Our project brings together an interdisciplinary team to study this issue with great public health, and clinical significance.